SSizer: Determining the Sample Sufficiency for Comparative Biological Study. Issue 11 (15th May 2020)

• Record Type: Journal Article
• Authors: Li, Fengcheng; Zhou, Ying; Zhang, Xiaoyu; Tang, Jing; Yang, Qingxia; Zhang, Yang; Luo, Yongchao; Hu, Jie; Xue, Weiwei; Qiu, Yunqing; He, Qiaojun; Yang, Bo; Zhu, Feng
• Is Part Of: Journal of molecular biology. Volume 432:Issue 11(2020)
• Page Start: 3411
• Page End: 3421
• Publication Date: 2020-05-15
• Subjects: sample size -- OMIC study -- power analysis -- diagnostic accuracy -- robustness; AUC area under the curve -- ACC classification accuracy -- CW weighted consistency -- OPLS-DA orthogonal partial least squares discriminant analysis -- PCA principal component analysis -- PLS-DA partial least squares-discriminant analysis -- ROC receiver operating characteristic; Molecular biology -- Periodicals; Biology -- Periodicals; Biochemistry -- Periodicals; Bacteriology -- Periodicals; Molecular Biology -- Periodicals; Biochemistry -- Periodicals; Biologie moléculaire -- Périodiques; Biologie -- Périodiques; Biochimie -- Périodiques; Moleculaire biologie; Biochemistry; Biology; Molecular biology; Periodicals; 572.805
• DOI: 10.1016/j.jmb.2020.01.027
• Languages: English
• ISSNs: 0022-2836

Abstract

Abstract: Comparative biological studies typically require plenty of samples to ensure full representation of the given problem. A frequently-encountered question is how many samples are sufficient for a particular study. This question is traditionally assessed using the statistical power, but it alone may not guarantee the full and reproducible discovery of features truly discriminating biological groups. Two new types of statistical criteria have thus been introduced to assess sample sufficiency from different perspectives by considering diagnostic accuracy and robustness . Due to the complementary nature of these criteria, a comprehensive evaluation based on all criteria is necessary for achieving a more accurate assessment. However, no such tool is available yet. Herein, an online tool SSizer (https://idrblab.org/ssizer/ ) was developed and validated to enable the assessment of the sample sufficiency for a user-input biological dataset, and three statistical criteria were adopted to achieve comprehensive and collective assessment. A sample simulation based on a user-input dataset was performed to expand the data and then determine the sample size required by the particular study. In sum, SSizer is unique for its ability to comprehensively evaluate whether the sample size is sufficient and determine the required number of samples for the user-input dataset, which, therefore, facilitates the comparative and OMIC-based biological studies. Graphical abstract: Image 1 Highlights: A key question in the current comparative biological study is how many samples are sufficient. A novel tool was developed to comprehensively evaluate sample sufficiency using multiple criteria. This new tool was unique in determining the required sample size for comparative biological study. The developed tool can facilitate the current comparative biological and OMIC-based studies.